Datasets:
| dataset_info: | |
| features: | |
| - name: images | |
| list: | |
| image: | |
| decode: false | |
| - name: image_group_id | |
| dtype: string | |
| - name: qa | |
| list: | |
| - name: inputs | |
| dtype: string | |
| - name: choices_list | |
| list: string | |
| - name: labels | |
| dtype: int64 | |
| - name: metadata | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 5769627677 | |
| num_examples: 94157 | |
| - name: validation | |
| num_bytes: 4020063 | |
| num_examples: 83 | |
| download_size: 5773110820 | |
| dataset_size: 5773647740 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: validation | |
| path: data/validation-* | |
| language: | |
| - en | |
| license: other | |
| source_datasets: [] | |
| task_categories: | |
| - multiple-choice | |
| - visual-question-answering | |
| tags: | |
| - decision-model | |
| - procedural | |
| license_name: tron-research-use | |
| license_link: https://github.com/YangTianze009/TRON#license | |
| # tron-mcq | |
| TRON MC keeps native images, options and labels, clarifying rounded measurements. | |
| Source: https://github.com/YangTianze009/TRON (research-use terms). Some geometry | |
| figures display rounded measurements while their source gold retains additional | |
| precision. Replace the exact two-decimal output request with a closest-offered-value | |
| MC instruction. Original questions remain in metadata. This repairs the pinned | |
| 100,000-QA mirror without regenerating any images or changing supervision. | |
| Original data: [original distribution](https://github.com/YangTianze009/TRON). Repackaged as parquet for [tasksource](https://github.com/sileod/tasksource) by [scripts/repackage_dataset/procedural/tron.py](https://github.com/sileod/tasksource/blob/main/scripts/repackage_dataset/procedural/tron.py#L128). | |
| [Conversion provenance](provenance.json): source revisions, hashes, configuration and exclusions. | |
| [Generation checkpoints](generation-checkpoints.json) record each chunk’s seeds and exclusions. Reproduce with the [resumable scale script](https://github.com/sileod/tasksource/blob/main/scripts/repackage_dataset/procedural/scale.py). | |